A real-time camera tracking algorithm using natural features for augmented reality applications is proposed. The system
relied on the passive vision techniques to obtain the camera pose online. A limited number of calibrated key-frames and
a rough 3D model of the part of the real environment were required. Accurate camera tracking could be achieved by
matching inputting image and the key-frame, whose viewpoint was as close as possible to the current one. Wide baseline
correspondence problem was solved by rendering intermediate image. Previous frames information was applied for jitter
correction. Algorithm performance was tested by real image sequences. Experimental results demonstrated that our
registration algorithm not only was accurate and robust, but also could handle significant aspect changes.